This paper promotes the use of panel data in nowcasting. We shift the existing focus of the literature, which has almost exclusively used time series models to nowcast national aggregate variables like gross domestic product (GDP). We propose a mixed-frequency panel VAR model and a...

We propose a new forecast combination method for panel data vector autoregressions that permit limited forms of parameterized heterogeneity (including fixed effects or incidental trends). Models are fitted using bias-corrected least squares in order to attenuate the effects of small sample bias...

We develop a new set of model selection methods for direct multistep forecasting of panel data vector autoregressive processes. Model selection is based on minimizing the estimated multistep quadratic forecast risk among candidate models. In order to attenuate the small sample bias of the least...

Traders in global markets operate at different local times-of-day. Suboptimal times-of-day may produce sleepiness due to daily variations in sleep/wake patterns and possibly also increased accumulation of hours awake. Global asset markets imply significantly increased heterogeneity in circadian...